Excitation-inhibition Ratio Research Articles

Functional excitation-inhibition ratio for social anxiety analysis and severity assessment.

Social anxiety disorder (SAD) is a prevalent psychiatric condition characterized by an intense fear of and avoidance of social situations. Traditional assessment methods for SAD primarily rely on subjective self-report questionnaires and clinical interviews, which can be prone to biases and inaccuracies. This study aims to explore the functional excitation-inhibition (fEI) ratio derived from EEG data as a potential objective biomarker for assessing SAD severity. Resting-state EEG data were collected from 20 control subjects and 60 individuals with varying degrees of SAD severity (mild, moderate, and severe). The fEI ratio was estimated across different EEG bands and analyzed, focusing on differences between control subjects and SAD groups. Significantly higher fEI ratios were observed in the alpha and low beta EEG bands in individuals with SAD compared to controls, especially within the prefrontal cortex. Additionally, a positive correlation was found between the fEI ratio and the severity of social anxiety symptoms across SAD severity levels. The findings indicate that the fEI ratio in the alpha and low beta bands may serve as a promising biomarker for assessing SAD severity. These results contribute to a deeper understanding of the neural mechanisms underlying social anxiety, offering a potentially more objective approach to SAD assessment compared to traditional methods.

Functional excitation-inhibition ratio indicates near-critical oscillations across frequencies

Abstract The concept of excitation/inhibition (E/I) balance plays an important role in understanding brain function in health and disease. We recently introduced an algorithm to determine a functional E/I ratio based on the critical brain dynamics that emerge in neuronal networks balancing between order and disorder. Little, however, is known about the frequency specificity of E/I regulation and how to measure it. Here, we optimized the algorithm for measuring functional excitation-inhibition ratio (fE/I) in narrow frequency ranges and validated it on a computational model of critical oscillations and EEG data. In the computational model, we confirmed that fE/I discriminated E/I connectivity differences across a wide range of frequencies (1–150 Hz). Twin EEG data revealed significant genetic influences on fE/I across frequencies, whereas contrasting eyes-open and -closed EEG indicated functional changes of fE/I restricted to a subset of alpha and beta oscillations and brain regions. We propose that assessing fE/I with finer frequency resolution will prove useful for understanding the functional role of E/I regulation in a spectrally refined fashion in health and disease.

In vivo whole-cortex marker of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth

A balanced excitation-inhibition ratio (E/I ratio) is critical for healthy brain function. Normative development of cortex-wide E/I ratio remains unknown. Here, we noninvasively estimate a putative marker of whole-cortex E/I ratio by fitting a large-scale biophysically plausible circuit model to resting-state functional MRI (fMRI) data. We first confirm that our model generates realistic brain dynamics in the Human Connectome Project. Next, we show that the estimated E/I ratio marker is sensitive to the gamma-aminobutyric acid (GABA) agonist benzodiazepine alprazolam during fMRI. Alprazolam-induced E/I changes are spatially consistent with positron emission tomography measurement of benzodiazepine receptor density. We then investigate the relationship between the E/I ratio marker and neurodevelopment. We find that the E/I ratio marker declines heterogeneously across the cerebral cortex during youth, with the greatest reduction occurring in sensorimotor systems relative to association systems. Importantly, among children with the same chronological age, a lower E/I ratio marker (especially in the association cortex) is linked to better cognitive performance. This result is replicated across North American (8.2 to 23.0 y old) and Asian (7.2 to 7.9 y old) cohorts, suggesting that a more mature E/I ratio indexes improved cognition during normative development. Overall, our findings open the door to studying how disrupted E/I trajectories may lead to cognitive dysfunction in psychopathology that emerges during youth.

Assessment of the excitation-inhibition ratio in the Fmr1 KO2 mouse using neuronal oscillation dynamics.

In vitro and ex vivo studies have shown consistent indications of hyperexcitability in the Fragile X Messenger Ribonucleoprotein 1 (Fmr1) knockout mouse model of autism spectrum disorder. We recently introduced a method to quantify network-level functional excitation-inhibition ratio from the neuronal oscillations. Here, we used this measure to study whether the implicated synaptic excitation-inhibition disturbances translate to disturbances in network physiology in the Fragile X Messenger Ribonucleoprotein 1 (Fmr1) gene knockout model. Vigilance-state scoring was used to extract segments of inactive wakefulness as an equivalent behavioral condition to the human resting-state and, subsequently, we performed high-frequency resolution analysis of the functional excitation-inhibition biomarker, long-range temporal correlations, and spectral power. We corroborated earlier studies showing increased high-frequency power in Fragile X Messenger Ribonucleoprotein 1 (Fmr1) knockout mice. Long-range temporal correlations were higher in the gamma frequency ranges. Contrary to expectations, functional excitation-inhibition was lower in the knockout mice in high frequency ranges, suggesting more inhibition-dominated networks. Exposure to the Gamma-aminobutyric acid (GABA)-agonist clonazepam decreased the functional excitation-inhibition in both genotypes, confirming that increasing inhibitory tone results in a reduction of functional excitation-inhibition. In addition, clonazepam decreased electroencephalogram power and increased long-range temporal correlations in both genotypes. These findings show applicability of these new resting-state electroencephalogram biomarkers to animal for translational studies and allow investigation of the effects of lower-level disturbances in excitation-inhibition balance.

Clinical and neuropsychological correlates of theta-band functional excitation-inhibition ratio in autism: An EEG study

ObjectiveHow abnormal brain signaling impacts cognition in autism spectrum disorder (ASD) remained elusive. This study aimed to investigate the local and global brain signaling in ASD indicated by theta-band functional excitation-inhibition (fE/I) ratio and explored psychophysiological relationships between fE/I, cognitive deficits, and ASD symptomatology. MethodsA total of 83 ASD and typically developing (TD) individuals participated in this study. Participants’ interference control and set-shifting abilities were assessed. Resting-state electroencephalography (EEG) was used for estimating theta-band fE/I ratio. ResultsASD individuals (n = 31 without visual EEG abnormality; n = 22 with visual EEG abnormality) generally performed slower in a cognitive task tapping interference control and set-maintenance abilities, but only ASD individuals with visually abnormal EEG performed significantly slower than their TD counterparts (Bonferroni-corrected ps < .001). Heightened theta-band fE/I ratios at the whole-head level, left and right hemispheres were observed in the ASD subgroup without visual EEG abnormality only (Bonferroni-corrected ps < .001), which remained highly significant when only data from medication-naïve participants were analyzed. In addition, higher left hemispheric fE/I ratios in ASD individuals without visual EEG abnormality were significantly correlated with faster interference control task performance, in turn faster reaction time was significantly associated with less severe restricted, repetitive behavior (Bonferroni-corrected ps ≤ .0017). ConclusionsDifferential theta-band fE/I within the ASD population. Heightened theta-band fE/I in ASD without visual EEG abnormality may be associated with more efficient filtering of distractors and a less severe ASD symptom manifestation. SignificanceBrain signaling, indicated by theta-band fE/I, was different in ASD subgroups. Only ASD with visually-normal EEG showed heightened theta-band fE/I, which was associated with faster processing of visual distractors during a cognitive task. More efficient distractor filtering was associated with less restricted, repetitive behaviors.

Circuit-level theories for sensory dysfunction in autism: convergence across mouse models.

Individuals with autism spectrum disorder (ASD) exhibit a diverse range of behavioral features and genetic backgrounds, but whether different genetic forms of autism involve convergent pathophysiology of brain function is unknown. Here, we analyze evidence for convergent deficits in neural circuit function across multiple transgenic mouse models of ASD. We focus on sensory areas of neocortex, where circuit differences may underlie atypical sensory processing, a central feature of autism. Many distinct circuit-level theories for ASD have been proposed, including increased excitation-inhibition (E-I) ratio and hyperexcitability, hypofunction of parvalbumin (PV) interneuron circuits, impaired homeostatic plasticity, degraded sensory coding, and others. We review these theories and assess the degree of convergence across ASD mouse models for each. Behaviorally, our analysis reveals that innate sensory detection behavior is heightened and sensory discrimination behavior is impaired across many ASD models. Neurophysiologically, PV hypofunction and increased E-I ratio are prevalent but only rarely generate hyperexcitability and excess spiking. Instead, sensory tuning and other aspects of neural coding are commonly degraded and may explain impaired discrimination behavior. Two distinct phenotypic clusters with opposing neural circuit signatures are evident across mouse models. Such clustering could suggest physiological subtypes of autism, which may facilitate the development of tailored therapeutic approaches.

Local signal variability and functional connectivity: Sensitive measures of the excitation-inhibition ratio?

The online version contains supplementary material available at 10.1007/s11571-023-10003-x.

Increased glutamate and glutamine levels and their relationship to astrocytes and dopaminergic transmissions in the brains of adults with autism

Increased excitatory neuronal tones have been implicated in autism, but its mechanism remains elusive. The amplified glutamate signals may arise from enhanced glutamatergic circuits, which can be affected by astrocyte activation and suppressive signaling of dopamine neurotransmission. We tested this hypothesis using magnetic resonance spectroscopy and positron emission tomography scan with 11C-SCH23390 for dopamine D1 receptors in the anterior cingulate cortex (ACC). We enrolled 18 male adults with high-functioning autism and 20 typically developed (TD) male subjects. The autism group showed elevated glutamate, glutamine, and myo-inositol (mI) levels compared with the TD group (p = 0.045, p = 0.044, p = 0.030, respectively) and a positive correlation between glutamine and mI levels in the ACC (r = 0.54, p = 0.020). In autism and TD groups, ACC D1 receptor radioligand binding was negatively correlated with ACC glutamine levels (r = − 0.55, p = 0.022; r = − 0.58, p = 0.008, respectively). The enhanced glutamate-glutamine metabolism might be due to astroglial activation and the consequent reinforcement of glutamine synthesis in autistic brains. Glutamine synthesis could underly the physiological inhibitory control of dopaminergic D1 receptor signals. Our findings suggest a high neuron excitation-inhibition ratio with astrocytic activation in the etiology of autism.

GABA, glutamate and excitatory-inhibitory ratios measured using short-TE STEAM MRS at 7-Tesla: Effects of macromolecule basis sets and baseline parameters

Rationale and objectivesMacromolecules (MMs) affect the precision and accuracy of neurochemical quantification in magnetic resonance spectroscopy. A measured MM basis is increasingly used in LCModel analysis combined with a spline baseline, whose stiffness is controlled by a parameter named DKNTMN. The effects of measured MM basis and DKNTMN were investigated. Materials and methodsTwenty-six healthy subjects were prospectively enrolled and scanned twice using a short echo-time Stimulated Echo Acquisition Mode (STEAM) at 7-T. Using LCModel, analyses were conducted using the simulated MM basis (MMsim) with DKNTMN 0.15 and an MM basis measured inhouse (MMmeas) with DKNTMN of 0.15, 0.30, 0.60 and 1.00. Cramér-Rao lower bound (CRLB) and the concentrations of gamma-aminobutyric acid (GABA), glutamate and excitatory-inhibitory ratio (EIR), in addition to MMs were statistically analyzed. Measurement stability was evaluated using coefficient of variation (CV). ResultsCRLBs of GABA were significantly lower when using MMsim than MMmeas; those of glutamate were 2–3. GABA concentrations were significantly higher in the analysis using MMsim than MMmeas where concentrations were significantly higher with DKNTMN of 0.15 or 0.30 than 0.60 or 1.00. Difference in glutamate concentration was not significant. EIRs showed the same difference as in GABA depending on the DKNTMN values. CVs between test-retest scans were relatively stable for glutamate but became larger as DKNTMN increased for GABA and EIR. ConclusionNeurochemical quantification depends on the parameters of the basis sets used for fitting. Analysis using MMmeas with DKNTMN of 0.30 conformed best to previous studies and is recommended.

Increased propensity for infantile spasms and altered neocortical excitation-inhibition balance in a mouse model of down syndrome carrying human chromosome 21

Children with Down syndrome (DS, trisomy of chromosome 21) have an increased risk of infantile spasms (IS). As an epileptic encephalopathy, IS may further impair cognitive function and exacerbate neurodevelopmental delays already present in children with DS. To investigate the pathophysiology of IS in DS, we induced IS-like epileptic spasms in a genetic mouse model of DS that carries human chromosome 21q, TcMAC21, the animal model most closely representing gene dosage imbalance in DS. Repetitive extensor/flexor spasms were induced by the GABAB receptor agonist γ-butyrolactone (GBL) and occurred predominantly in young TcMAC21 mice (85%) but also in some euploid mice (25%). During GBL application, background electroencephalographic (EEG) amplitude was reduced, and rhythmic, sharp-and-slow wave activity or high-amplitude burst (epileptiform) events emerged in both TcMAC21 and euploid mice. Spasms occurred only during EEG bursts, but not every burst was accompanied by a spasm. Electrophysiological experiments revealed that basic membrane properties (resting membrane potential, input resistance, action-potential threshold and amplitude, rheobase, input-output relationship) of layer V pyramidal neurons were not different between TcMAC21 mice and euploid controls. However, excitatory postsynaptic currents (EPSCs) evoked at various intensities were significantly larger in TcMAC21 mice than euploid controls, while inhibitory postsynaptic currents (IPSCs) were similar between the two groups, resulting in an increased excitation-inhibition (E-I) ratio. These data show that behavioral spasms with epileptic EEG activity can be induced in young TcMAC21 DS mice, providing proof-of-concept evidence for increased IS susceptibility in these DS mice. Our findings also show that basic membrane properties are similar in TcMAC21 and euploid mice, while the neocortical E-I balance is altered to favor increased excitation in TcMAC21 mice, which may predispose to IS generation.

Preservation of thalamocortical circuitry is essential for good recovery after cardiac arrest.

Continuous electroencephalographam (EEG) monitoring contributes to prediction of neurological outcome in comatose cardiac arrest survivors. While the phenomenology of EEG abnormalities in postanoxic encephalopathy is well known, the pathophysiology, especially the presumed role of selective synaptic failure, is less understood. To further this understanding, we estimate biophysical model parameters from the EEG power spectra from individual patients with a good or poor recovery from a postanoxic encephalopathy. This biophysical model includes intracortical, intrathalamic, and corticothalamic synaptic strengths, as well as synaptic time constants and axonal conduction delays. We used continuous EEG measurements from hundred comatose patients recorded during the first 48 h postcardiac arrest, 50 with a poor neurological outcome [cerebral performance category ] and 50 with a good neurological outcome ( ). We only included patients that developed (dis-)continuous EEG activity within 48 h postcardiac arrest. For patients with a good outcome, we observed an initial relative excitation in the corticothalamic loop and corticothalamic propagation that subsequently evolved towards values observed in healthy controls. For patients with a poor outcome, we observed an initial increase in the cortical excitation-inhibition ratio, increased relative inhibition in the corticothalamic loop, delayed corticothalamic propagation of neuronal activity, and severely prolonged synaptic time constants that did not return to physiological values. We conclude that the abnormal EEG evolution in patients with a poor neurological recovery after cardiac arrest may result from persistent and selective synaptic failure that includes corticothalamic circuitry and also delayed corticothalamic propagation.

Opposing retrograde and astrocyte-dependent endocannabinoid signaling mechanisms regulate lateral habenula synaptic transmission

The lateral habenula (LHb) encodes aversive states, and its dysregulation is implicated in neuropsychiatric disorders, including depression. The endocannabinoid (eCB) system is a neuromodulatory signaling system that broadly serves to counteract the adverse effects of stress; however, CB1 receptor signaling within the LHb can paradoxically promote anxiogenic- and depressive-like effects. Current reports of synaptic actions of eCBs in the LHb are conflicting and lack systematic investigation of eCB regulation of excitatory and inhibitory transmission. Here, we report that eCBs differentially regulate glutamatergic and GABAergic transmission in the LHb, exhibiting canonical and circuit-specific inhibition of both systems and an opposing potentiation of synaptic glutamate release mediated via activation of CB1 receptors on astrocytes. Moreover, simultaneous depression of GABA and potentiation of glutamate release increases the net excitation-inhibition ratio onto LHb neurons, suggesting a potential cellular mechanism by which cannabinoids may promote LHb activity and subsequent anxious- and depressive-like aversive states.

SCN1A gain of function causes interneuron hyperexcitability and network instability through inhibitory synaptic plasticity in early infantile encephalopathy.

SCN1A gain-of-function variants are associated with early infantile and neonatal-onset developmental and epileptic encephalopathies (DEE). It is unclear how SCN1A gain-of-function may predispose to cortical hyper-excitability and seizures. We studied the biophysical properties of four pathogenic Nav1.1 variants associated with neonatal-onset (T162I, I236V) or early infantile (P1345S, R1636Q) DEE. In voltage clamp experiments, the activation curves of the variants were either unchanged (T236V), or exhibited hyperpolarized shifts (T162I, P1345S, R1636Q), corresponding to gain-of-function through enhanced window currents. Inactivation curves were unchanged (I236V, P1345S), depolarized, suggesting gain-of-function (R1636Q), or hyperpolarized, suggesting loss-of-function (T162I). Dynamic action potential clamp experiments supported a gain of function mechanism for all variants. Model neurons incorporating Nav1.1. channels with properties of I236V, P1345S, or R1636Q variants exhibited higher and sustained firing relative to wild type, whereas T162I exhibited enhanced early action potential firing and depolarization block. T162I and R1636Q produced a hyperpolarized threshold and reduced neuronal rheobase. To explore the impact of SCN1A variants upon cortical excitability, we used a cortical network model containing excitatory pyramidal cells, PV interneurons and realistic synaptic connectivity. SCN1A gain-of-function was modelled by enhancing PV excitability and incorporating a simple form of homeostatic adaptation: inhibitory synaptic plasticity. Although both wild-type and gain-of-function networks possessed similar basal pyramidal cell firing rates, the gain-of-function network was more sensitive to external perturbation and exhibited synchronous epileptiform-like activity. Further analysis revealed that reduced synaptic strength results in a deficit of feedback inhibition and an increased excitatory-inhibitory ratio in the gain-of-function network. Overall, our findings support the role of SCN1A gain-of-function in early onset DEE. We propose a mechanism through which homeostatic adaptations in neuronal networks can predispose to enhanced excitatory activity and seizures.

Estimating functional excitation-inhibition ratios during electroconvulsive therapy

Estimating functional excitation-inhibition ratios during electroconvulsive therapy

An increase of inhibition drives the developmental decorrelation of neural activity.

Throughout development, the brain transits from early highly synchronous activity patterns to a mature state with sparse and decorrelated neural activity, yet the mechanisms underlying this process are poorly understood. The developmental transition has important functional consequences, as the latter state is thought to allow for more efficient storage, retrieval, and processing of information. Here, we show that, in the mouse medial prefrontal cortex (mPFC), neural activity during the first two postnatal weeks decorrelates following specific spatial patterns. This process is accompanied by a concomitant tilting of excitation-inhibition (E-I) ratio toward inhibition. Using optogenetic manipulations and neural network modeling, we show that the two phenomena are mechanistically linked, and that a relative increase of inhibition drives the decorrelation of neural activity. Accordingly, in mice mimicking the etiology of neurodevelopmental disorders, subtle alterations in E-I ratio are associated with specific impairments in the correlational structure of spike trains. Finally, capitalizing on EEG data from newborn babies, we show that an analogous developmental transition takes place also in the human brain. Thus, changes in E-I ratio control the (de)correlation of neural activity and, by these means, its developmental imbalance might contribute to the pathogenesis of neurodevelopmental disorders.

Keeping Excitation-Inhibition Ratio in Balance.

Unrelated genetic mutations can lead to convergent manifestations of neurological disorders with similar behavioral phenotypes. Experimental data frequently show a lack of dramatic changes in neuroanatomy, indicating that the key cause of symptoms might arise from impairment in the communication between neurons. A transient imbalance between excitatory (glutamatergic) and inhibitory (GABAergic) synaptic transmission (the E/I balance) during early development is generally considered to underlie the development of several neurological disorders in adults. However, the E/I ratio is a multidimensional variable. Synaptic contacts are highly dynamic and the actual strength of synaptic projections is determined from the balance between synaptogenesis and synaptic elimination. During development, relatively slow postsynaptic receptors are replaced by fast ones that allow for fast stimulus-locked excitation/inhibition. Using the binomial model of synaptic transmission allows for the reassessing of experimental data from different mouse models, showing that a transient E/I shift is frequently counterbalanced by additional pre- and/or postsynaptic changes. Such changes—for instance, the slowing down of postsynaptic currents by means of immature postsynaptic receptors—stabilize the average synaptic strength, but impair the timing of information flow. Compensatory processes and/or astrocytic signaling may represent possible targets for medical treatments of different disorders directed to rescue the proper information processing.

Tau reduction affects excitatory and inhibitory neurons differently, reduces excitation/inhibition ratios, and counteracts network hypersynchrony.

SUMMARYThe protein tau has been implicated in many brain disorders. In animal models, tau reduction suppresses epileptogenesis of diverse causes and ameliorates synaptic and behavioral abnormalities in various conditions associated with excessive excitation-inhibition (E/I) ratios. However, the underlying mechanisms are unknown. Global genetic ablation of tau in mice reduces the action potential (AP) firing and E/I ratio of pyramidal cells in acute cortical slices without affecting the excitability of these cells. Tau ablation reduces the excitatory inputs to inhibitory neurons, increases the excitability of these cells, and structurally alters their axon initial segments (AISs). In primary neuronal cultures subjected to prolonged overstimulation, tau ablation diminishes the homeostatic response of AISs in inhibitory neurons, promotes inhibition, and suppresses hypersynchrony. Together, these differential alterations in excitatory and inhibitory neurons help explain how tau reduction prevents network hypersynchrony and counteracts brain disorders causing abnormally increased E/I ratios.

Propagation of spiking regularity in feedforward networks with recurrent connections

The regularity of the inter-spike intervals (ISIs) gives a critical window into how the information is coded temporally in the cortex. Previous researches mostly adopt pure feedforward networks (FFNs) to study how the network structure affects spiking regularity propagation, which ignore the role of local dynamics within the layer. In this paper, we construct an FFN with recurrent connections and investigate the propagation of spiking regularity. We argue that an FFN with recurrent connections serves as a basic circuit to explain that the regularity increases as spikes propagate from middle temporal visual areas to higher cortical areas. We find that the reduction of regularity is related to the decreased complexity of the shared activity co-fluctuations. We show in simulations that there is an appropriate excitation–inhibition ratio maximizing the regularity of deeper layers. Furthermore, it is demonstrated that collective temporal regularity in deeper layers exhibits resonance-like behavior with respect to both synaptic connection probability and synaptic weight. Our work provides a critical link between cortical circuit structure and realistic spiking regularity.

Distinct hierarchical alterations of intrinsic neural timescales account for different manifestations of psychosis.

Hierarchical perceptual-inference models of psychosis may provide a holistic framework for understanding psychosis in schizophrenia including heterogeneity in clinical presentations. Particularly, hypothesized alterations at distinct levels of the perceptual-inference hierarchy may explain why hallucinations and delusions tend to cluster together yet sometimes manifest in isolation. To test this, we used a recently developed resting-state fMRI measure of intrinsic neural timescale (INT), which reflects the time window of neural integration and captures hierarchical brain gradients. In analyses examining extended sensory hierarchies that we first validated, we found distinct hierarchical INT alterations for hallucinations versus delusions in the auditory and somatosensory systems, thus providing support for hierarchical perceptual-inference models of psychosis. Simulations using a large-scale biophysical model suggested local elevations of excitation-inhibition ratio at different hierarchical levels as a potential mechanism. More generally, our work highlights the robustness and utility of INT for studying hierarchical processes relevant to basic and clinical neuroscience.

Frequency-dependent response in cortical network with periodic electrical stimulation.

Electrical stimulation can shape oscillations in brain activity. However, the mechanism of how periodic electrical stimulation modulates brain oscillations by time-delayed neural networks is poorly understood at present. To address this question, we investigate the effects of periodic stimulations on the oscillations generated via a time-delayed neural network. We specifically study the effect of unipolar and asymmetric bidirectional pulse stimulations by altering amplitude and frequency in a systematic manner. Our findings suggest that electrical stimulations play a central role in altering oscillations in the time-delayed neural network and that these alterations are strongly dependent on the stimulus frequency. We observe that the time-delayed neural network responds differently as the stimulation frequency is altered, as manifested by changes in resonance, entrainment, non-linear oscillation, or oscillation suppression. The results also indicate that the network presents similar response activities with increasing stimulus frequency under different excitation-inhibition ratios. Collectively, our findings pave the way for exploring the potential mechanism underlying the frequency-dependent modulation of network activity via electrical stimulations and provide new insights into possible electrical stimulation therapies to the neurological and psychological disorders in clinical practice.